Closed Knowledge Loop
A feedback system where discovery, explanation, and generalization continuously inform and improve each other.
Category: General AI/ML
Metaheuristic
A high-level problem-solving framework that provides a set of guidelines or strategies to develop heuristic optimization algorithms.
Explainable AI
A set of processes and methods that make the outputs of AI systems understandable to humans.
Flexible Job Shop Scheduling
A complex scheduling problem where jobs must be assigned to machines with varying capabilities and constraints to optimize performance metrics.
Adaptive Operator Evolution
A method that allows operators in Evolutionary Algorithms to evolve and adapt dynamically based on the performance and state of the population.
Improvement Prompting Strategies
Techniques used to provide suggestions for enhancing the performance of operators based on their current effectiveness.
Dynamic Operator Design
An adaptive approach to designing operators in Evolutionary Algorithms that changes based on the current state of the search process.
Knowledge Transfer
The process of applying knowledge gained in one context to a different but related context, often used to enhance learning and performance.
Evolutionary Algorithm
A class of optimization algorithms inspired by the process of natural selection, used to solve complex problems by iteratively improving candidate solutions.
Two-Stage Training Strategy
A training approach that includes an initial training phase followed by a fine-tuning phase using reinforcement learning.